Hanford 300 Area Beryllium Exposure Maps
Produced by CRESP
as of November 2002
UW Hanford Activities
A related CRESP report: "Hanford Building Leasing Program: Identified Procedural Improvements".
 
Click to read a brief description or a full description of these maps and the mapping process.
Maps
Table

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PowerPoint file - hbemaps11.2002.ppt
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Click to view the table which corresponds to the maps.

Also available in .pdf format - bemaptable11.2002.pdf
   

Also available are the Beryllium Exposure Maps produced in September, 2001.

A related CRESP report is also available: "The Hanford Building Leasing Program: Identified Procedural Improvements".

This is a .PDF document. If you do not have Acrobat Reader, click to install the free program.

 

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Use of Risk Density Mapping to Refine Risk Estimates for
Beryllium Exposure at Hanford

(This is a brief description. Click to read the full text)
Kathy Ertell*, Tim Takaro*, Katie Omri*, Lee Newman**, Elaine Faustman, Terry Kavanaugh.

CRESP - University of Washington; *University of Washington Occupational & Environmental Medicine Program;**National Jewish Medical and Research Center, Occupational Medicine.

Abstract
Beryllium was used in nuclear fuel rod research and manufacturing at the US Department of Energy's (US DOE) Hanford site in eastern Washington from approximately 1950 to 1988. With the increased recognition of chronic beryllium disease as an occupational health issue, there has been great interest in identifying buildings where beryllium was used and characterizing risk for workers. Although there are workplace exposure records indicating where beryllium was used at Hanford, the records are not believed to be a complete picture of beryllium work at Hanford. Using job histories, an exposure matrix, results of medical screening tests (beryllium LPT) for both current and retired Hanford workers, and recent building characterization data, risk density maps of Hanford work locations have been produced. These maps show person-years of beryllium exposure and job titles by work location for both sensitized and nonsensitized exposed workers. By combining and comparing these multiple sources of information for the risk density mapping, the list of building where beryllium was used has been refined; information about the types of work performed by sensitized workers has been gathered; and the work locations for beryllium-exposed workers have been defined in greater depth. The results of the risk density mapping will help prioritize future building characterization, guide work planning for decontamination and decommissioning; and refine risk estimates for current and former workers.

Risk Density Mapping Rationale

  • Beryllium was recognized as a renewed exposure concern in the mid 1990s.
  • Site buildings have undergone sampling (wipe and air) to determine the level of beryllium contamination in buildings where beryllium was used in the past.
  • As buildings undergo maintenance or D&D, additional characterization of inner spaces and inaccessible areas is being done.
  • Risk density mapping can help prioritize ongoing characterizations.
Beryllium Risk Density Mapping Goals:
  • Identify higher risk buildings in 300 Area for D&D, maintenance workers.
  • Provide framework for combining beryllium data sets from different sources.
  • Utilize sensitized workers as sentinel events to suggest risk associated with building, and ultimately task within building or operation.
  • Provide a readily accessible format for describing risk to workers.
Methods
Using two major data sources, a job exposure matrix and occupational history questionnaires, person-years of potential beryllium exposure were summed for each building in the beryllium operations period. Person-years are color coded on the maps. Superimposed are asterisks indicating where sentinel cases with beryllium sensitization or disease have worked. The number represents jobs in a building performed by a sensitized worker. Each job is counted once, but a sensitized worker may have several jobs in the 300 Area and may have worked in several different buildings. Separate maps were produced for each data source, and a combined map of overlaps was produced.
(This is a brief description. Click for the full text)

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